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Record W2032416910 · doi:10.1145/1920778.1920817

PiNiZoRo

2010· article· en· W2032416910 on OpenAlexafffund
Kevin G. Stanley, Ian J. Livingston, Alan Bandurka, Robert Kapiszka, Regan L. Mandryk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsEnthusiasmRecreationLeverage (statistics)Global Positioning SystemMultimediaComputer scienceFocus (optics)Human–computer interactionFocus groupMobile devicePsychologyWorld Wide WebSociologySocial psychologyArtificial intelligencePolitical scienceTelecommunications

Abstract

fetched live from OpenAlex

Obesity is a growing problem among children, due in part to their sedentary lifestyles. Time spent engaged in physical activity is decreasing, while time spent playing computer and video games is on the rise. We leverage children's interest in digital games to encourage families to engage in purposeful walking. We present a GPS-based game, played on a mobile device that uses walking as a primary gameplay mechanic. Our game, PiNiZoRo, includes a fighting game, triggered at points along a real-world route, and a map editor that allows parents and recreation specialists to create custom routes in their neighbourhoods. Results from an initial focus group with parents were positive, as they showed enthusiasm for the concept, implementation, and gameplay.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.163
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1630.030

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.256
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations47
Published2010
Admission routes2
Has abstractyes

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